Improving predictive maintenance benefits from online monitoring of spindles: case study in woodworking machine tool

Autores/as

  • Thyago Bachim Uninove University, Industrial Engineering Post Graduation Program, São Paulo, São Paulo, Brazil https://orcid.org/0000-0002-8982-545X
  • Mauro Luiz Martens Uninove University, Industrial Engineering Post Graduation Program, São Paulo, São Paulo, Brazil https://orcid.org/0000-0003-1242-8795
  • Salvatore Digiesi Polytechnic University of Bari, Department of Mechanics, Mathematics and Management, Bari, Italy
  • Douglas Favero Trindade SKF do Brasil Ltda – Spindle Service - Cajamar - SP
  • Bruno Ricci SKF do Brasil Ltda – Spindle Service - Cajamar – SP

DOI:

https://doi.org/10.20397/2177-6652/2020.v20i4.2009

Palabras clave:

Spindle, Maintenance, Industry 4.0, Online Monitoring, Internet of Things, IoT

Resumen

Objective: This article aims to present a case study of the application of an online monitoring system for spindles in a furniture industry, analyzing the benefits to predictive maintenance and business.

 

Methodology/approach: A literature review was carried out followed by a case study

 

Originality/Relevance: Focusing the development of maintenance techniques, especially predictive maintenance and those supported by enabling technologies from Industry 4.0, such as Internet of Things (IoT), it may be possible to carry out online monitoring of spindles with a focus on reducing catastrophic or unplanned events.

 

Main results: The main results are to know the normal behavior of the machine, the possibility of obtaining information in real time, managerial data for sight management, and the possibility of identifying spindle failure before it becomes a catastrophic failure, thus reducing the costs of maintaining the spindles.

 

Theoretical contributions: As a contribution, we discuss the development of the system to digitize the data through the operation available in an outsourced cloud environment. This data can then be returned to the company in the form of dashboards for cash management, developing agility in decision making to facilitate the predictive maintenance in addition to validating the online monitoring system for spindle management in furniture industry processes.

Biografía del autor/a

Thyago Bachim, Uninove University, Industrial Engineering Post Graduation Program, São Paulo, São Paulo, Brazil

University Nove de Julho, Industrial Engineering Post Graduation Program, São Paulo, São Paulo, Brazil

 

Mauro Luiz Martens, Uninove University, Industrial Engineering Post Graduation Program, São Paulo, São Paulo, Brazil

Mauro Luiz Martens is a Full Professor and Director of the Industrial Engineering Post Graduation Department at University Nove de Julho (UNINOVE), , in Brazil.  He holds a PhD in Production Engineering from the Polytechnic School of the University of São Paulo (USP), Brazil. He was a Visiting Scholar at Bentley University in 2014. He is a CNPq researcher looking at the relations between project management, sustainability and Industry 4.0.

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Publicado

2020-11-24

Cómo citar

Bachim, T., Martens, M. L., Digiesi, S., Trindade, D. F., & Ricci, B. (2020). Improving predictive maintenance benefits from online monitoring of spindles: case study in woodworking machine tool. Revista Gestão & Tecnologia, 20(4), 7–34. https://doi.org/10.20397/2177-6652/2020.v20i4.2009

Número

Vol. 20 Núm. 4 (2020): Outubro/Dezembro

Sección

ARTIGO

Licencia

Derechos de autor 2020 Journal of Management & Technology

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